We investigate the power properties of a new goodness-of-fit testproposed by Foutz (1980). This new test is compared with the Chi squaredtest and the Kolmogorov-Smirnov (K-S) test for normality when the samplescome from (i) the family of asymmetric stable distributions, (ii) mixturesof normal distributions, and (iii) the Pearson family. The general conclusionis that the new test performs better than the Chi squared and theK-S test when the parent distribution is heavy-tailed. If the hypothesizeddistribution differs from the true distribution in location only,the new test does not do as well as the other two.
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